Posts Tagged ‘Data governance’
Records Retention in the Age of AI: Why Taxonomy Still Reigns Supreme
In a world increasingly shaped by artificial intelligence (AI), records retention has moved from back-office obligation to strategic necessity. AI systems thrive on data, but not just any data—relevant, accurate, well-structured data. Without intentional retention policies, organizations risk feeding their AI outdated, redundant or even harmful information, leading to flawed outputs and questionable decisions. This…
Read MoreAI and Data Engineering
The rise of artificial intelligence (AI) has fundamentally reshaped data engineering, turning what was once a largely pipeline-focused discipline into a dynamic, intelligence-driven ecosystem. On the upside, it has accelerated everything. Data ingestion is faster with automated schema detection. Data quality tools now flag anomalies in real time. Pipeline orchestration has become smarter, predicting failures…
Read MoreHow Governance and AI Tame the Unstructured Wild
Unstructured data is everywhere — emails, PDFs, videos, social posts, call transcripts, and meeting notes. Basically, it is in all the places your organization hides the good stuff while pretending spreadsheets run the world. The challenge is not a lack of information. It is the inability to consistently organize, trust and use it. This important…
Read MoreGarbage In, Genius Out? Not Without Data Governance
Generative artificial intelligence (GenAI) is having a moment. It writes, summarizes, predicts, designs and occasionally makes you question your own job security before your coffee kicks in. But beneath all the flash and promise is something far less glamorous and far more important: data governance. Because no matter how sophisticated your AI tools are, they…
Read MoreAI Isn’t Magic. It’s Just Really Fast at Repeating Your Mistakes.
Artificial intelligence (AI) gets a lot of hype. It can write your emails, summarize your meetings and occasionally sound like it just read a philosophy book. But what it absolutely will not do is fix your chaotic, dusty, “we’ll deal with it later” data situation. FedScoop brought this topic to us in their article, “The…
Read MoreGarbage In, Chaos Out: The Sneaky Problem of AI Data Poisoning
Artificial intelligence (AI) is everywhere right now, quietly helping make decisions behind the scenes. But here’s the catch: it’s only as smart as the data we feed it. And sometimes, that data is not exactly trustworthy. This topic came to us from The Conversation and their article, “What is AI poisoning? A computer scientist explains.” Enter…
Read MoreThe Quiet Chaos Wrecking Your Decisions
Dirty data is everywhere. Duplicate records, missing info, outdated details and just plain wrong data quietly piling up behind the scenes. Each issue seems small, but together they can completely derail decisions, trust and day-to-day operations. This interesting topic came to us from IBM in their article, “What is dirty data?“ The tricky part? It…
Read MoreThe Pace of Technology
Technology continues to advance at a rapid rate, driven by developments in artificial intelligence (AI), cloud services, connected devices and emerging research fields such as quantum computing. These innovations create new possibilities for efficiency, insight and global collaboration, while also increasing the complexity of managing and protecting data. This interesting topic came to us from…
Read MoreAligning AI
Artificial intelligence (AI) is changing how organizations operate and make decisions. However, most existing governance frameworks were designed for traditional data management and risk control, not for systems that learn and evolve on their own. To manage AI responsibly, organizations must expand their governance models to include ethical oversight, transparency and accountability for automated decision-making.…
Read MoreGenAI Runs on Trust
Generative artificial intelligence (GenAI), a subset of artificial intelligence (AI), has moved quickly from experimentation to everyday use, reshaping how organizations create, analyze and communicate. At the center of this shift is data. The quality, structure and oversight of that data now directly influence how reliable and responsible AI outputs can be. This makes data…
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